24 Association of Research Libraries Research Library Issues 298 — 2019 Access Policy for faculty publications have all been informed by DSE efforts.11 Outside of a professional Master’s Program in Data Science, geared toward retraining students returning to the workforce, the UW MSDSE did not set out to create a separate degree program. Rather, it took the approach that data science education should reside within the departments. At both the undergraduate and graduate levels, departments have ownership of the tools and techniques of data science that enhance their programs, and have the options and flexibility to implement what is most beneficial in their curricula. In contrast to UC Berkeley, UW started developing its data science curriculum at the doctoral level. At UW, there was a pre-existing category referred to as a “transcriptable option,” similar to a minor, that could be recognized on a student’s transcript. This option, used at both the graduate and undergraduate level, allows a student to take a small number of data- focused courses in key data-science areas (such as statistics, machine learning, data management, data visualization, and ethics/privacy) in addition to their chosen major. Upon completion, the student receives a statement on his or her transcript—for example, “Bachelor of Science in Bioengineering, Data Science Option.” In looking for ways to expand data science techniques into the disciplines, UW has put much of its energy into its Incubator Program and Data Science for Social Good. Both programs match a researcher who is studying an existing problem with a group of data scientists who can help with the data-intensive part of the work. And both programs bring together a diverse set of participants who learn from one another, across disciplines, to help solve problems. Conclusion Each of the three MSDSE sites has had significant interaction and collaboration with their university library. At both NYU and UW, the newly designed data science centers were established in library